scholarly journals Recent Development and Challenges in Spectroscopy and Machine Vision Technologies for Crop Nitrogen Diagnosis: A Review

2020 ◽  
Vol 12 (16) ◽  
pp. 2578
Author(s):  
Daoliang Li ◽  
Pan Zhang ◽  
Tao Chen ◽  
Wei Qin
Keyword(s):  
Machine Vision ◽  
State Of The Art ◽  
Accurate Diagnosis ◽  
Optical Methods ◽  
Estimation Methods ◽  
Advantages And Disadvantages ◽  
System Selection ◽  
Future Work ◽  
Non Destructive ◽  
N Status

Recent development of non-destructive optical techniques, such as spectroscopy and machine vision technologies, have laid a good foundation for real-time monitoring and precise management of crop N status. However, their advantages and disadvantages have not been systematically summarized and evaluated. Here, we reviewed the state-of-the-art of non-destructive optical methods for monitoring the N status of crops, and summarized their advantages and disadvantages. We mainly focused on the contribution of spectral and machine vision technology to the accurate diagnosis of crop N status from three aspects: system selection, data processing, and estimation methods. Finally, we discussed the opportunities and challenges of the application of these technologies, followed by recommendations for future work to address the challenges.

scholarly journals Machine Vision for Ripeness Estimation in Viticulture Automation

Horticulturae ◽  
2021 ◽  
Vol 7 (9) ◽  
pp. 282
Author(s):  
Eleni Vrochidou ◽  
Christos Bazinas ◽  
Michail Manios ◽  
George A. Papakostas ◽  
Theodore P. Pachidis ◽  
...  
Keyword(s):  
Machine Vision ◽  
Fruits And Vegetables ◽  
State Of The Art ◽  
Cost Effective ◽  
Future Trends ◽  
Broad Area ◽  
Wide Range ◽  
Key Factor ◽  
Non Destructive ◽  
Destructive Methods

Ripeness estimation of fruits and vegetables is a key factor for the optimization of field management and the harvesting of the desired product quality. Typical ripeness estimation involves multiple manual samplings before harvest followed by chemical analyses. Machine vision has paved the way for agricultural automation by introducing quicker, cost-effective, and non-destructive methods. This work comprehensively surveys the most recent applications of machine vision techniques for ripeness estimation. Due to the broad area of machine vision applications in agriculture, this review is limited only to the most recent techniques related to grapes. The aim of this work is to provide an overview of the state-of-the-art algorithms by covering a wide range of applications. The potential of current machine vision techniques for specific viticulture applications is also analyzed. Problems, limitations of each technique, and future trends are discussed. Moreover, the integration of machine vision algorithms in grape harvesting robots for real-time in-field maturity assessment is additionally examined.

scholarly journals A Review of the State-of-Art, Limitations, and Perspectives of Machine Vision for Grape Ripening Estimation

2021 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Eleni Vrochidou ◽  
Christos Bazinas ◽  
George A. Papakostas ◽  
Theodore Pachidis ◽  
Vassilis G. Kaburlasos
Keyword(s):  
Machine Vision ◽  
State Of The Art ◽  
The State ◽  
Wine Industry ◽  
Ripening Stage ◽  
Robotic Automation ◽  
Non Destructive ◽  
State Of Art ◽  
Destructive Methods ◽  
Critical Aspects

This work highlights the most recent machine vision methodologies and algorithms proposed for estimating the ripening stage of grapes. Destructive and non-destructive methods are overviewed for in-field and in-lab applications. Integration principles of innovative technologies and algorithms to agricultural agrobots, namely, Agrobots, are investigated. Critical aspects and limitations, in terms of hardware and software, are also discussed. This work is meant to be a complete guide of the state-of-the-art machine vision algorithms for grape ripening estimation, pointing out the advantages and barriers for the adaptation of machine vision towards robotic automation of the grape and wine industry.

Platelet monitoring for PCI

2009 ◽  
Vol 29 (04) ◽  
pp. 376-380 ◽  
Author(s):  
D. Capodanno ◽  
D. J. Angiolillo
Keyword(s):  
Interindividual Variability ◽  
State Of The Art ◽  
Coronary Intervention ◽  
Functional Tests ◽  
Treatment Regimens ◽  
Advantages And Disadvantages ◽  
Coronary Syndrome ◽  
Combined Use ◽  
Increased Risk ◽  
Percutaneous Coronary

SummaryDespite the clinical benefit associated with the combined use of aspirin and clopidogrel in patients with acute coronary syndrome or those undergoing percutaneous coronary intervention, a considerable interindividual variability in response to these drugs have been consistently reported. There is a growing interest on applying platelet functional tests with the goal of identifying patients at increased risk of recurrent ischaemic events and potentially tailoring antiplatelet treatment regimens.This manuscript will review the state of the art on the most commonly available platelet functional tests, describing their advantages and disadvantages and exploring their applicability in clinical practice.

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

scholarly journals Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Short Wave ◽  
Machine Learning Algorithms ◽  
Estimation Methods ◽  
Chemical Information ◽  
Tea Quality ◽  
The Mean ◽  
Processing Techniques ◽  
Spectral Patterns ◽  
Physical And Chemical ◽  
Non Destructive

AbstractSpectroscopic sensing provides physical and chemical information in a non-destructive and rapid manner. To develop non-destructive estimation methods of tea quality-related metabolites in fresh leaves, we estimated the contents of free amino acids, catechins, and caffeine in fresh tea leaves using visible to short-wave infrared hyperspectral reflectance data and machine learning algorithms. We acquired these data from approximately 200 new leaves with various status and then constructed the regression model in the combination of six spectral patterns with pre-processing and five algorithms. In most phenotypes, the combination of de-trending pre-processing and Cubist algorithms was robustly selected as the best combination in each round over 100 repetitions that were evaluated based on the ratio of performance to deviation (RPD) values. The mean RPD values were ranged from 1.1 to 2.7 and most of them were above the acceptable or accurate threshold (RPD = 1.4 or 2.0, respectively). Data-based sensitivity analysis identified the important hyperspectral regions around 1500 and 2000 nm. Present spectroscopic approaches indicate that most tea quality-related metabolites can be estimated non-destructively, and pre-processing techniques help to improve its accuracy.

scholarly journals Inductive Thermography as Non-Destructive Testing for Railway Rails

2021 ◽  
Vol 11 (3) ◽  
pp. 1003
Author(s):  
Christoph Tuschl ◽  
Beate Oswald-Tranta ◽  
Sven Eck
Keyword(s):  
Eddy Current ◽  
Electrical Discharge Machining ◽  
Rolling Contact ◽  
Heat Diffusion ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Ir Camera ◽  
Advantages And Disadvantages ◽  
Average Crack ◽  
Non Destructive

Inductive thermography is a non-destructive testing method, whereby the specimen is slightly heated with a short heating pulse (0.1–1 s) and the temperature change on the surface is recorded with an infrared (IR) camera. Eddy current is induced by means of high frequency (HF) magnetic field in the surface ‘skin’ of the specimen. Since surface cracks disturb the eddy current distribution and the heat diffusion, they become visible in the IR images. Head checks and squats are specific types of damage in railway rails related to rolling contact fatigue (RCF). Inductive thermography can be excellently used to detect head checks and squats on rails, and the method is also applicable for characterizing individual cracks as well as crack networks. Several rail pieces with head checks, with artificial electrical discharge-machining (EDM)-cuts and with a squat defect were inspected using inductive thermography. Aiming towards rail inspection of the track, 1 m long rail pieces were inspected in two different ways: first via a ‘stop-and-go’ technique, through which their subsequent images are merged together into a panorama image, and secondly via scanning during a continuous movement of the rail. The advantages and disadvantages of both methods are compared and analyzed. Special image processing tools were developed to automatically fully characterize the rail defects (average crack angle, distance between cracks and average crack length) in the recorded IR images. Additionally, finite element simulations were used to investigate the effect of the measurement setup and of the crack parameters, in order to optimize the experiments.

scholarly journals A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5248
Author(s):  
Aleksandra Pawlicka ◽  
Marek Pawlicki ◽  
Rafał Kozik ◽  
Ryszard S. Choraś
Keyword(s):  
Systematic Review ◽  
Recommender Systems ◽  
Recommender System ◽  
State Of The Art ◽  
The State ◽  
Advantages And Disadvantages ◽  
Comprehensive Survey ◽  
Security Concerns ◽  
Valuable Role

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

scholarly journals A Machine Vision Approach for Bioreactor Foam Sensing

2021 ◽  
pp. 247263032110088
Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Vision ◽  
State Of The Art ◽  
Low Cost ◽  
High Accuracy ◽  
Consumer Electronics ◽  
Learning System ◽  
Automotive Applications ◽  
Fine Grained

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.

scholarly journals Summer Research Placements – State-of-the-Art Science by pre-University Students

MRS Advances ◽  
2016 ◽  
Vol 1 (56) ◽  
pp. 3715-3720 ◽  
Author(s):  
R. A. Sporea ◽  
S. Lygo-Baker
Keyword(s):  
University Students ◽  
State Of The Art ◽  
Group Learning ◽  
Student Interaction ◽  
Research Tool ◽  
Skills Acquisition ◽  
Advantages And Disadvantages ◽  
Effective Training ◽  
Training And Research ◽  
Student Training

ABSTRACTSummer research placements are an effective training and research tool. Over three years, our group has hosted nine pre-university students over periods of four to six weeks. Apart from student training and skills acquisition, the placements have produced several peer-reviewed technical publications. Our approach relies on careful pre-planning of activities, frequent student interaction, coupled with independent and group learning. We explore the advantages and disadvantages of this manner of running summer placements.

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